Expand description
Dense clustering primitives.
clump provides clustering algorithms for dense f32 vectors, generic over
a pluggable distance metric.
Batch: Kmeans, Dbscan, Hdbscan, EVoC, CopKmeans,
CorrelationClustering.
Streaming: MiniBatchKmeans, DenStream.
Re-exports§
pub use cluster::ClusterHierarchy;pub use cluster::ClusterLayer;pub use cluster::ClusterNode;pub use cluster::CompositeDistance;pub use cluster::Constraint;pub use cluster::CopKmeans;pub use cluster::CorrelationClustering;pub use cluster::CorrelationResult;pub use cluster::CosineDistance;pub use cluster::Dbscan;pub use cluster::DenStream;pub use cluster::DistanceMetric;pub use cluster::EVoC;pub use cluster::EVoCParams;pub use cluster::Euclidean;pub use cluster::Hdbscan;pub use cluster::InnerProductDistance;pub use cluster::Kmeans;pub use cluster::KmeansFit;pub use cluster::MiniBatchKmeans;pub use cluster::SignedEdge;pub use cluster::SquaredEuclidean;pub use cluster::NOISE;pub use error::Error;pub use error::Result;